A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets

Model-Informed Radiopharmaceutical Therapy Optimization: A Study on the Impact of PBPK Model Parameters on Physical, Biological, and Statistical Measures in 177Lu-PSMA Therapy

Purpose: To investigate the impact of physiologically based pharmacokinetic (PBPK) parameters on physical, biological, and statistical measures in lutetium-177-labeled radiopharmaceutical therapies (RPTs) targeting the prostate-specific membrane antigen (PSMA). Methods: Using a clinically validated PBPK model, realistic time-activity curves (TACs) for tumors, salivary glands, and kidneys were generated based on various model parameters. These TACs were used to calculate the area-under-the-TAC (AUC), dose, biologically effective dose (BED), and figure-of-merit BED (fBED). The effects of these parameters on radiobiological, pharmacokinetic, time, and statistical features were assessed. Results: Manipulating PBPK parameters significantly influenced AUC, dose, BED, and fBED outcomes across four different BED models. Higher association rates increased AUC, dose, and BED values for tumors, with minimal impact on non-target organs. Increased internalization rates reduced AUC and dose for tumors and kidneys. Higher serum protein-binding rates decreased AUC and dose for all tissues. Elevated tumor receptor density and ligand amounts enhanced uptake and effectiveness in tumors. Larger tumor volumes required dosimetry adjustments to maintain efficacy. Setting the tumor release rate to zero intensified the impact of association and internalization rates, enhancing tumor targeting while minimizing the effects on salivary glands and kidneys. Conclusions: Optimizing PBPK parameters can enhance the efficacy of lutetium-177-labeled RPTs targeting PSMA, providing insights for personalized and effective treatment regimens to minimize toxicity and improve therapeutic outcomes.

Understanding Relative Biological Effectiveness and Clinical Outcome of Prostate Cancer Therapy Using Particle Irradiation: Analysis of Tumor Control Probability With the Modified Microdosimetric Kinetic Model

PURPOSE

Recent experimental studies and clinical trial results might indicate that-at least for some indications-continued use of the mechanistic model for relative biological effectiveness (RBE) applied at carbon ion therapy facilities in Europe for several decades (LEM-I) may be unwarranted. We present a novel clinical framework for prostate cancer treatment planning and tumor control probability (TCP) prediction based on the modified microdosimetric kinetic model (mMKM) for particle therapy.

METHODS AND MATERIALS

Treatment plans of 91 patients with prostate tumors (proton: 46, carbon ions: 45) applying 66 GyRBE [RBE = 1.1 for protons and LEM-I, (α/β)x = 2.0 Gy, for carbon ions] in 20 fractions were recalculated using mMKM [(α/β)x = 3.1 Gy]). Based solely on the response data of photon-irradiated patient groups stratified according to risk and usage of androgen deprivation therapy, we derived parameters for an mMKM-based Poisson-TCP model. Subsequently, new carbon and helium ion plans, adhering to prescribed biological dose criteria, were generated. These were systematically compared with the clinical experience of Japanese centers employing an analogous fractionation scheme and existing proton plans.

RESULTS

mMKM predictions suggested significant biological dose deviation between the proton and carbon ion arms. Patients irradiated with protons received (3.25 ± 0.08)  GyRBEmMKM/Fx, whereas patients treated with carbon ions received(2.51 ± 0.05)  GyRBEmMKM/Fx. TCP predictions were (86 ± 3)% for protons and (52 ± 4)% for carbon ions, matching the clinical outcome of 85% and 50%. Newly optimized carbon ion plans, guided by the mMKM/TCP model, effectively replicated clinical data from Japanese centers. Using mMKM, helium ions exhibited similar target coverage as proton and carbon ions and improved rectum and bladder sparing compared with proton.

CONCLUSIONS

Our mMKM-based model for prostate cancer treatment planning and TCP prediction was validated against clinical data for proton and carbon ion therapy, and its application was extended to helium ion therapy. Based on the data presented in this work, mMKM seems to be a good candidate for clinical biological calculations in carbon ion therapy for prostate cancer.

Evaluation of Tumor Control and Normal Tissue Complication Probabilities in Patients Receiving Comprehensive Nodal Irradiation for Left-Sided Breast Cancer

Women with left-sided breast cancer receiving adjuvant radiotherapy have increased incidence of cardiac mortality due to ischemic heart disease; to date, no threshold dose for late cardiac/pulmonary morbidity or mortality has been established. We investigated the likelihood of cardiac death and radiation pneumonitis in women with left-sided breast cancer who received comprehensive lymph node irradiation. The differences in dosimetric parameters between free-breathing (FB) and deep inspiration breath hold (DIBH) techniques were also addressed. Based on NTCP calculations, the probability of cardiac death was significantly reduced with the DIBH compared to the FB technique (p < 0.001). The risk of radiation pneumonitis was not clinically significant. There was no difference in coverage between FB and DIBH plans. Doses to healthy structures were significantly lower in DIBH plan than in FB plan for V20, V30, and ipsilateral total lung volume. Inspiratory gating reduces the dose absorbed by the heart without compromising the target range, thus reducing the likelihood of cardiac death.

Artificial neural network-assisted prediction of radiobiological indices in head and neck cancer

Background and purpose

We proposed an artificial neural network model to predict radiobiological parameters for the head and neck squamous cell carcinoma patients treated with radiation therapy. The model uses the tumor specification, demographics, and radiation dose distribution to predict the tumor control probability and the normal tissue complications probability. These indices are crucial for the assessment and clinical management of cancer patients during treatment planning.

Methods

Two publicly available datasets of 31 and 215 head and neck squamous cell carcinoma patients treated with conformal radiation therapy were selected. The demographics, tumor specifications, and radiation therapy treatment parameters were extracted from the datasets used as inputs for the training of perceptron. Radiobiological indices are calculated by open-source software using dosevolume histograms from radiation therapy treatment plans. Those indices were used as output in the training of a single-layer neural network. The distribution of data used for training, validation, and testing purposes was 70, 15, and 15%, respectively.

Results

The best performance of the neural network was noted at epoch number 32 with the mean squared error of 0.0465. The accuracy of the prediction of radiobiological indices by the artificial neural network in training, validation, and test phases were determined to be 0.89, 0.87, and 0.82, respectively. We also found that the percentage volume of parotid inside the planning target volume is the significant parameter for the prediction of normal tissue complications probability.

Conclusion

We believe that the model has significant potential to predict radiobiological indices and help clinicians in treatment plan evaluation and treatment management of head and neck squamous cell carcinoma patients.

Impact of Dose Calculation Algorithms and Radiobiological Parameters on Prediction of Cardiopulmonary Complications in Left Breast Radiation Therapy

Background

Breast cancer requires evaluating treatment plans using dosimetric and biological parameters. Considering radiation dose distribution and tissue response, healthcare professionals can optimize treatment plans for better outcomes.

Objective

This study aimed to evaluate the effects of the different Dose Calculation Algorithms (DCAs) and Biologically Model-Related Parameters (BMRPs) on the prediction of cardiopulmonary complications due to left breast radiotherapy.

Material and Methods

In this practical study, the treatment plans of 21 female patients were simulated in the Monaco Treatment Planning System (TPS) with a prescribed dose of 50 Gy in 25 fractions. Dose distribution was extracted using the three DCAs [Pencil Beam (PB), Collapsed Cone (CC), and Monte Carlo (MC)]. Cardiopulmonary complications were predicted by Normal Tissue Complication Probability (NTCP) calculations using different dosimetric and biological parameters. The Lyman-Kutcher-Burman (LKB) and Relative-Seriality (RS) models were used to calculate NTCP. The endpoint for NTCP calculation was pneumonitis, pericarditis, and late cardiac mortality. The ANOVA test was used for statistical analysis.

Results

In calculating Tumor Control Probability (TCP), a statistically significant difference was observed between the results of DCAs in the Poisson model. The PB algorithm estimated NTCP as less than others for all Pneumonia BMRPs.

Conclusion

The impact of DCAs and BMRPs differs in the estimation of TCP and NTCP. DCAs have a stronger influence on TCP calculation, providing more effective results. On the other hand, BMRPs are more effective in estimating NTCP. Consequently, parameters for radiobiological indices should be cautiously used s to ensure the appropriate consideration of both DCAs and BMRPs.

A systematic review of the normal tissue complication probability models and parameters: Head and neck cancers treated with conformal radiotherapy

This systematic review study aims to provide comprehensive data on different radiobiological models, parameters, and endpoints used for calculating the normal tissue complication probability (NTCP) based on clinical data from head and neck cancer patients treated with conformal radiotherapy. A systematic literature search was carried out according to the PRISMA guideline for the identification of relevant publications in six electronic databases of Embase, PubMed, Scopus, and Google Scholar to July 2022 using specific keywords in the paper's title and abstract. The initial search resulted in 1368 articles for all organs for the review article about the NTCP parameters. One hundred and seventy-eight articles were accepted for all organs with complete parameters for the mentioned models and finally, 20 head and neck cancer articles were accepted for review. Analysis of the studies shows that the Lyman-Kutcher-Burman (LKB) model properly links the NTCP curve parameters to the postradiotherapy endpoints. In the LKB model for esophagus, the minimum, and maximum corresponding parameters were reported as TD50  = 2.61 Gy with grade ≥3 radiation-induced esophagitis endpoints as the minimum TD50 and TD50  = 68 Gy as the maximum ones. nmin  = 0.06, nmax  = 1.04, mmin  = 0.1, and mmax  = 0.65, respectively. Unfortunately, there was not a wide range of published articles on other organs at risk like ear or cauda equina except Burman et al. (Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys Ther. 1991;21:123-135). Findings suggest that the validation of different radiobiological models and their corresponding parameters need to be investigated in vivo and in vitro for developing a more accurate NTCP model to be used for radiotherapy treatment planning optimization.

ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions

BACKGROUND AND OBJECTIVES

Radiotherapy prescriptions currently derive from population-wide guidelines established through large clinical trials. We provide an open-source software tool for patient-specific prescription determination using personalized dose-response curves.

METHODS

We developed ROE, a plugin to the Computational Environment for Radiotherapy Research to visualize predicted tumor control and normal tissue complication simultaneously, as a function of prescription dose. ROE can be used natively with MATLAB and is additionally made accessible in GNU Octave and Python, eliminating the need for commercial licenses. It provides a curated library of published and validated predictive models and incorporates clinical restrictions on normal tissue outcomes. ROE additionally provides batch-mode tools to evaluate and select among different fractionation schemes and analyze radiotherapy outcomes across patient cohorts.

CONCLUSION

ROE is an open-source, GPL-copyrighted tool for interactive exploration of the dose-response relationship to aid in radiotherapy planning. We demonstrate its potential clinical relevance in (1) improving patient awareness by quantifying the risks and benefits of a given treatment protocol (2) assessing the potential for dose escalation across patient cohorts and (3) estimating accrual rates of new protocols.

Patient-specific three-dimensional image reconstruction from a single X-ray projection using a convolutional neural network for on-line radiotherapy applications

Background and purpose: Radiotherapy is commonly chosen to treat thoracic and abdominal cancers. However, irradiating mobile tumors accurately is extremely complex due to the organs' breathing-related movements. Different methods have been studied and developed to treat mobile tumors properly. The combination of X-ray projection acquisition and implanted markers is used to locate the tumor in two dimensions (2D) but does not provide three-dimensional (3D) information. The aim of this work is to reconstruct a high-quality 3D computed tomography (3D-CT) image based on a single X-ray projection to locate the tumor in 3D without the need for implanted markers. Materials and Methods: Nine patients treated for a lung or liver cancer in radiotherapy were studied. For each patient, a data augmentation tool was used to create 500 new 3D-CT images from the planning four-dimensional computed tomography (4D-CT). For each 3D-CT, the corresponding digitally reconstructed radiograph was generated, and the 500 2D images were input into a convolutional neural network that then learned to reconstruct the 3D-CT. The dice score coefficient, normalized root mean squared error and difference between the ground-truth and the predicted 3D-CT images were computed and used as metrics. Results: Metrics' averages across all patients were 85.5% and 96.2% for the gross target volume, 0.04 and 0.45 Hounsfield unit (HU), respectively. Conclusions: The proposed method allows reconstruction of a 3D-CT image from a single digitally reconstructed radiograph that could be used in real-time for better tumor localization and improved treatment of mobile tumors without the need for implanted markers.

Machine learning for normal tissue complication probability prediction: Predictive power with versatility and easy implementation

Background and purpose

A popular Normal tissue Complication (NTCP) model deployed to predict radiotherapy (RT) toxicity is the Lyman-Burman Kutcher (LKB) model of tissue complication. Despite the LKB model's popularity, it can suffer from numerical instability and considers only the generalized mean dose (GMD) to an organ. Machine learning (ML) algorithms can potentially offer superior predictive power of the LKB model, and with fewer drawbacks. Here we examine the numerical characteristics and predictive power of the LKB model and compare these with those of ML.

Materials and methods

Both an LKB model and ML models were used to predict G2 Xerostomia on patients following RT for head and neck cancer, using the dose volume histogram of parotid glands as the input feature. Model speed, convergence characteristics and predictive power was evaluated on an independent training set.

Results

We found that only global optimization algorithms could guarantee a convergent and predictive LKB model. At the same time our results showed that ML models remained unconditionally convergent and predictive, while staying robust to gradient descent optimization. ML models outperform LKB in Brier score and accuracy but compare to LKB in ROC-AUC.

Conclusion

We have demonstrated that ML models can quantify NTCP better than or as well as LKB models, even for a toxicity that the LKB model is particularly well suited to predict. ML models can offer this performance while offering fundamental advantages in model convergence, speed, and flexibility, and so could offer an alternative to the LKB model that could potentially be used in clinical RT planning decisions.

Contralateral esophageal sparing technique in definitive radiotherapy for non-small cell lung cancer: dosimetric parameters and normal tissue complication probability modeling

Background

The purpose of this study was to assess the benefit of the contralateral esophageal sparing technique (CEST) in definitive radiotherapy of non-small cell lung cancer (NSCLC).

Materials and methods

We retrospectively reviewed radiation plans for 13 patients who underwent definitive chemoradiation for locally advanced NSCLC. Alternative plans were prepared with the use of CEST, with an additional margin of 5 mm from planning treatment volume (PTV). Normal tissue complication probability (NTCP) analyses for the esophagus and tumor control probability (TCP) for the PTV were performed for original and CEST plans using the equivalent uniform dose (EUD)-based mathematical model.

Results

In all cases, the CEST plan allowed for the reduction of esophageal dose, with a mean of 3.8 Gy (range, 0.7 to 8.7 Gy). The mean reductions of V40 and V60 to the esophagus were 6.4 Gy (range, 2.1 to 17.2 Gy) and 1.9 Gy (range, 3.4 to 10.0 Gy), respectively. There was no substantial decrease in the maximal dose to the esophagus. Reduction of NTCP was achieved for all patients (range, 5-73%), and TCP was not affected (-1.8 to +6.7%).

Conclusions

The application of CEST in definitive radiotherapy of locally advanced NSCLC allows for reducing selected dosimetric parameters to the esophagus without compromising TCP.

Predictive modelling for late rectal and urinary toxicities after prostate radiotherapy using planned and delivered dose

Background and purpose

Normal tissue complication probability (NTCP) parameters derived from traditional 3D plans may not be ideal in defining toxicity outcomes for modern radiotherapy techniques. This study aimed to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively scored clinical data for late gastrointestinal (GI) and genitourinary (GU) toxicities for high-risk prostate cancer patients treated using volumetric-modulated-arc-therapy (VMAT). Dose-volume-histograms (DVH) extracted from planned (D_P) and accumulated dose (D_A) were used.

Material and methods

D_P and D_A obtained from the DVH of 150 prostate cancer patients with pelvic-lymph-nodes irradiation treated using VMAT were used to generate LKB-NTCP parameters using maximum likelihood estimations. Defined GI and GU toxicities were recorded up to 3-years post RT follow-up. Model performance was measured using Hosmer-Lemeshow goodness of fit test and the mean area under the receiver operating characteristics curve (AUC). Bootstrapping method was used for internal validation.

Results

For mild-severe (Grade ≥1) GI toxicity, the model generated similar parameters based on D_A and D_P DVH data (D_A-D₅₀:71.6 Gy vs D_P-D₅₀:73.4; D_A-m:0.17 vs D_P-m:0.19 and D_A/P-n 0.04). The 95% CI for D_A-D₅₀ was narrower and achieved an AUC of >0.6. For moderate-severe (Grade ≥2) GI toxicity, D_A-D₅₀ parameter was higher and had a narrower 95% CI (D_A-D₅₀:77.9 Gy, 95% CI:76.4-79.6 Gy vs D_P-D₅₀:74.6, 95% CI:69.1-85.4 Gy) with good model performance (AUC>0.7). For Grade ≥1 late GU toxicity, D₅₀ and n parameters for D_A and D_P were similar (D_A-D₅₀: 58.8 Gy vs D_P-D₅₀: 59.5 Gy; D_A-n: 0.21 vs D_P-n: 0.19) with a low AUC of<0.6. For Grade ≥2 late GU toxicity, similar NTCP parameters were attained from D_A and D_P DVH data (D_A-D₅₀:81.7 Gy vs D_P-D₅₀:81.9 Gy; D_A-n:0.12 vs D_P-n:0.14) with an acceptable AUCs of >0.6.

Conclusions

The achieved NTCP parameters using modern RT techniques and accounting for organ motion differs from QUANTEC reported parameters. D_A-D₅₀ of 77.9 Gy for GI and D_A/D_P-D₅₀ of 81.7-81.9 Gy for GU demonstrated good predictability in determining the risk of Grade ≥2 toxicities especially for GI derived D₅₀ and are recommended to incorporate as part of the DV planning constraints to guide dose escalation strategies while minimising the risk of toxicity.

A Dosimetric and Radiobiological Comparison of Intensity Modulated Radiotherapy, Volumetric Modulated Arc Therapy and Helical Tomotherapy Planning Techniques in Synchronous Bilateral Breast Cancer

OBJECTIVE

The present investigation intends to identify the optimal radiotherapy treatment plan for synchronous bilateral breast cancer (SBBC) using dosimetric and radiobiological indexes for three techniques, namely, helical tomotherapy (HT), volumetric modulated arc therapy (VMAT), and intensity-modulated radiotherapy (IMRT).

METHODS

Twenty SBBC treated female patients treatment planning data (average age of 52.5 years) were used as the sample for the present study. Three different plans were created using 50 Gy in a 25 fraction dose regime. Poisson, Niemierko, and LKB models were applied for calculating normal tissue complication probability (NTCP) and tumour control probability (TCP).

RESULT

The target average dose comparison between IMRT with HT and VMAT with HT was highly substantial (P=0.001). The percentage of TCP for IMRT, VMAT, and HT in the Poisson model were 93.70±0.28, 94.68±0.30, and 94.34±0.57, respectively (p<0.05). The dose maximum was lower for the whole lung in the HT plan, with an average dose of 49.31Gy±3.9 (p<0.009). The NTCP values of both Niemierko and LKB models were lower for the heart, lungs, and liver for the IMRT plan.

CONCLUSION

The sparing of organs at risk was higher in the HT plan dosimetrically, and the TCP was higher in the three techniques. The comparison between the three techniques shows that the IMRT and HT techniques could be considered for treating SBBC.

Introducing new plan evaluation indices for prostate dose painting IMRT plans based on apparent diffusion coefficient images

BACKGROUND

Dose painting planning would be more complicated due to different levels of prescribed doses and more complex evaluation with conventional plan quality indices considering uniform dose prescription. Therefore, we tried to introduce new indices for evaluating the dose distribution conformity and homogeneity of treatment volumes based on the tumoral cell density and relative volumes of each lesion in prostate IMRT.

METHODS

CT and MRI scans of 20 male patients having local prostate cancer were used for IMRT DP planning. Apparent diffusion coefficient (ADC) images were imported to a MATLAB program to identify lesion regions based on ADC values automatically. Regions with ADC values lower than 750 mm²/s and regions with ADC values higher than 750 and less than 1500 mm²/s were considered CTV_70Gy (clinical tumor volume with 70 Gy prescribed dose), and CTV_60Gy, respectively. Other regions of the prostate were considered as CTV_53Gy. New plan evaluation indices based on evaluating the homogeneity (IOE(H)), and conformity (IOE(C)) were introduced, considering the relative volume of each lesion and cellular density obtained from ADC images. These indices were compared with conventional homogeneity and conformity indices and IOEs without considering cellular density. Furthermore, tumor control probability (TCP) was calculated for each patient, and the relationship of the assessed indices were evaluated with TCP values.

RESULTS

IOE (H) and IOE (C) with considering cellular density had significantly lower values compared to conventional indices and IOEs without considering cellular density. (P < 0.05). TCP values had a stronger relationship with IOE(H) considering cell density (R² = -0.415), and IOE(C) without considering cell density (R² = 0.624).

CONCLUSION

IOE plan evaluation indices proposed in this study can be used for evaluating prostate IMRT dose painting plans. We suggested to consider cell densities in the IOE(H) calculation formula and it's appropriate to calculate IOE(C) without considering cell density values.

On the calculation of the relative biological effectiveness of ion radiation therapy using a biological weighting function, the microdosimetric kinetic model (MKM) and subsequent corrections (non-Poisson MKM and modified MKM)

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE α of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

A Novel Radiotherapeutic Approach to Treat Bulky Metastases Even From Cutaneous Squamous Cell Carcinoma: Its Rationale and a Look at the Reliability of the Linear-Quadratic Model to Explain Its Radiobiological Effects

Introduction

Metastatic cutaneous squamous cell carcinoma (cSCC) is a very rare condition. The lack of definition of an oligometastatic subgroup means that there is no consensus for its treatment, unlike the mucosal head and neck counterpart. Like the latter, the cutaneous form is able to develop bulky tumor masses. When this happens, the classic care approach is just for palliative intent due to a likely unfavorable benefit–risk balance typical of aggressive treatments. Here we proposed a novel radiotherapy (RT) technique to treat bulky metastases from cSCC in the context of an overall limited tumor burden and tried to explain its clinical outcome by the currently available mathematical radiobiological and ad hoc developed models.

Methods

We treated a case of facial cSCC with three metastases: two of them by classic stereotactic RT and the other by lattice RT supported by metabolic imaging (¹⁸F-FDG PET) due to its excessively large dimensions. For the latter lesion, we compared four treatment plans with different RT techniques in order to define the best approach in terms of normal tissue complication probability (NTCP) and tumor control probability (TCP). Moreover, we developed an ad hoc mathematical radiobiological model that could fit better with the characteristics of heterogeneity of this bulky metastasis for which, indeed, a segmentation of normoxic, hypoxic, and necrotic subvolumes might have been assumed.

Results

We observed a clinical complete response in all three disease sites; the bulky metastasis actually regressed more rapidly than the other two treated by stereotactic RT. For the large lesion, NTCP predictions were good for all four different plans but even significantly better for the lattice RT plan. Neither the classic TCP nor the ad hoc developed radiobiological models could be totally adequate to explain the reported outcome. This finding might support a key role of the host immune system.

Conclusions

PET-guided lattice RT might be safe and effective for the treatment of bulky lesions from cSCC. There might be some need for complex mathematical radiobiological models that are able to take into account any immune system’s role in order to explain the possible mechanisms of the tumor response to radiation and the relevant key points to enhance it.

Dosimetric Comparison and TCP-NTCP Modeling for Lung, Heart, Left Anterior Descending, and Right Coronary Artery in Left-sided Breast Cancer Conventional and Hypofractionated Radiotherapy

Background: The aim of this study was to evaluate the dose distribution, as well as tumor control probability (TCP) and normal tissue complications probability (NTCP) models for females with left-sided breast cancer for 3D-CRT, 6, and 9 fields intensity modulated radiotherapy (IMRT) and hypofractionated tangential plans. Methods: Eighty females with left-sided breast cancer (N1T1 – N3T3) were included in this study. The patients were divided into breast conserving surgery (BCS) (n= 50) and mastectomy (n=30) patients. CT simulation images of the patients were imported on the treatment planning software (TiGRT, LinaTech, China) and the tangential treatment plans of the mentioned methods were done, using TPS. Dose assessments were performed, employing the TPS, and TCP-NTCP models of stated modalities were done, using Poisson linear-quadatric (PLQ) and Lyman-Kutcher-Burman (LKB) models on MATLAB and R software. Results: For the BCS and post-mastectomy patients, 6FIMRT imposed lower doses to ipsilateral lung, heart, LAD, RCA, and contralateral breast compared to 9FIMRT, hypofractionated RT, and 3D-CRT (P < 0.005). Also, the NTCPs of the mentioned normal tissues for 6FIMRT were lower than other methods for both BCS and post-mastectomy groups. Moreover, it was found that the V20Gy for Ipsilateral lung and the V25Gy for heart, LAD, and RCA of 6FIMRT, 9FIMRT, and hypofractionated RT was significantly lower compared to 3D-CRT (P < 0.005) for both BCS and mastectomy groups, while there were no significant differences among them for the 6FIMRT and 9FIMRT with hypofractionated RT (P > 0.005). The TCP values of 9FIMRT, 6FIMRT, and hypofractionated RT were not considerably different; however, the TCP values of 3D-CRT were lower compared to other stated methods. Conclusions: 6FIMRT is a suitable choice for RT of patients with left-sided breast cancer compared to other mentioned modalities, as a result of providing adequate PTV dose coverage and TCPs. Also, it may impose lower doses and NTCPs for OARs. Hypofractionated RT is a good alternative to reduce treatment time for patients with breast cancer.

Diagnostic Application and Systematic Evaluation of Image Registration Software in External Radiotherapy

Purpose: Analyze the clinical application of MIM maestro in cancer radiotherapy and evaluate the advantage of the software compare to the clinical applied tools. Materials and Methods: Potentially relevant studies published were identified through a pubmed and web of science search using words “MIM Maestro,” “Atlas,” “image registration,” “dose accumulation,” “irradiation.” Combinations of words were also searched as were bibliographies of downloaded papers in order to avoid missing relevant publications. Results: In many patients with cancer radiotherapy, multiple types of images are demanded, MIM Maestro is a multi-modality image information processing system for radiotherapy. Contour atlas and image registration among dose accumulation and individual fractions is beneficial for radiotherapy. Overall 34 papers were enrolled for analysis. The MIM appears to provide excellent clinical applications such as the function of contour altas, image fusion and registration, dose accumulation in radiotherapy compared to the other software. Conclusions: The regular optimization of radiotherapy technology and the development of image technology, improve the clinical efficiency. The current paper give a systematic review of MIM Maestro multi-modality image processing software.

Pediatric Craniospinal Irradiation - The implementation and Use of Normal Tissue Complication Probability in Comparing Photon versus Proton Planning

Purpose:

The preferred radiotherapy treatment for medulloblastoma is craniospinal irradiation (CSI). With the aim of developing the potential to reduce normal tissue dose and associated post-treatment complications with photon and proton radiotherapy techniques for CSI. This report aims to carefully compare and rank treatment planning and dosimetric outcomes for pediatric medulloblastoma patients using normal tissue complication probability (NTCP) formalism between photon (three-dimensional conformal radiotherapy, intensity-modulated radiotherapy [IMRT], volumetric-modulated arc therapy [VMAT], and HT) and proton CSI.

Methods and Materials:

The treatment data of eight pediatric patients who typically received CSI treatment were used in this study. The patients were 7 years of age on average, with ages ranging from 3 to 11 years. A prescription dose of 3600 cGy was delivered in 20 fractions by the established planning methods. The Niemierko's and Lyman–Kutcher–Burman models were followed to carefully estimate NTCP and compare different treatment plans.

Results:

The NTCP of VMAT plans in upper and middle thoracic volumes was relatively high compared to helical tomotherapy (HT) and pencil beam scanning (PBS) (all P < 0.05). PBS rather than IMRT and VMAT in the middle thoracic region (P < 0.06) could significantly reduce the NTCP of the heart. PBS significantly reduced NTCP of the lungs and liver (all P < 0.05).

Conclusion:

The NTCP and tumor control probability (TCP) model-based plan ranking along with dosimetric indices will help the clinical practitioner or medical physicists to choose the best treatment plan for each patient based on their anatomical or clinical challenges.

Analysis of a cohort of prostate patients treated with HDR mono-brachytherapy

The aim of this study is to perform volumetric and basic radiobiological analyses using the database on prostate patients treated by HDR brachytherapy in our institution during the period 2011-2016. Real-time ultrasound based technique was used, with Oncentra Prostate planning software. The whole period was divided into two sub-periods, according to the 100% dose per fraction, which was 10.5 Gy during the first period (2011-2012), and 11 Gy during the second period (2013-2016), for each of the three fractions. The follow up time varied from 19 to 81 months, with a median of 45 months and a mean of 47 months. The uniformity of the treatment technique for both periods is investigated. Tumour Control Probability (TCP) values for the expected local control are calculated according to a population phenomenological TCP model for different values of the α/β ratio. The calculations are based on the obtained averaged Dose Volume Histograms for the two investigated sub-periods. 74 patients were treated in total. Local control failure is observed in 5 cases, which corresponds to an observed TCP = 93.2%. The comparison of the calculated population average DVH with the DVHs of the cases with local control failure shows that in 4 of them, doses higher than average were delivered to the prostate. It is shown that the uniformity of the treatment was improved during the second sub-period. A possible explanation of the observed failures may be that these cases exhibit inherent tumour cell radio-resistance higher than average. Our radiobiological analysis indicates a α/β ratio value somewhat higher than the one currently accepted. The value of the prostate α/β ratio is estimated to be in the range of [3.5-6] Gy.

Evaluating different radiotherapy treatment plans, in terms of critical organ scoring index, conformity index, tumor control probability, and normal tissue complication probability calculations in early glottic larynx carcinoma

Purpose

In this study, it is aimed to compare three different radiotherapy treatment planning techniques in terms of critical organ scoring index (COSI), two different conformity index (CI), tumor control probability (TCP), and normal tissue complication probability (NTCP) calculations in early (T1) glottic larynx carcinoma (T1GL). Furthermore, it is aimed to investigate these parameters compliance with dose-volume histograms (DVH) parameters.

Materials and Methods

Ten T1GL patients were immobilized in a supine position with a head and neck thermoplastic mask. Treatment plans were created with opposed lateral fields (OLAFs) and intensity-modulated radiation therapy (IMRT) techniques with a total dose of 66 Gy in 33 fraction with 2 Gy/day. IMRT fields were selected as five fields (5IMRT) and seven fields (7IMRT). Dosimetric evaluation of three different treatment plans for T1GL carcinoma was performed in two consequential steps. First step was the assessment of planning target volume (PTV), all organs at risks (OARs), and normal tissue (NT) dose calculations according to given dose constraint directions and comparing the plans via DVH. In the second step, for PTV, the compatibility of DVH data with CIs-TCP was investigated where COSI-NTCP was compared with DVH for OARs. The DVH data were considered as reference in all evaluations.

Results

The CI_RTOG mean values were significantly closer to 1 with IMRT plans when compared to OLAF plans (P = 0.005). The CI_PADDICK mean values revealed that OLAF plans were significantly worse than IMRT plans (P = 0.005). No statistically significant difference was found between all three plans in terms of homogeneity index mean values (P = 0.076). The calculated mean TCP values were significantly better for 7IMRT plans when compared to OLAF and 5IMRT plans (P = 0.007 and P = 0.017, respectively). Both NTCP and COSI evaluations, which is compatible with DVH, significantly favored OLAF plan for spinal cord and 7IMRT for thyroid gland. The COSI evaluations, which are compatible with DVH, significantly favored 7IMRT plan for carotid arteries and 5IMRT plan for NT.

Conclusion

Our results demonstrated that CI_PADDICK-TCP calculations for PTV and COSI-NTCP calculations for OARs were compatible with DVH in T1 GL plans. Therefore, we suggest such parameters as valuable tools for choosing the feasible one among multiple plans and even with different treatment machines.

Tumor Control Probability Modeling and Systematic Review of the Literature of Stereotactic Body Radiation Therapy for Prostate Cancer

PURPOSE

Dose escalation improves localized prostate cancer disease control, and moderately hypofractionated external beam radiation is noninferior to conventional fractionation. The evolving treatment approach of ultrahypofractionation with stereotactic body radiation therapy (SBRT) allows possible further biological dose escalation (biologically equivalent dose [BED]) and shortened treatment time.

METHODS AND MATERIALS

The American Association of Physicists in Medicine Working Group on Biological Effects of Hypofractionated Radiation Therapy/SBRT included a subgroup to study the prostate tumor control probability (TCP) with SBRT. We performed a systematic review of the available literature and created a dose-response TCP model for the endpoint of freedom from biochemical relapse. Results were stratified by prostate cancer risk group.

RESULTS

Twenty-five published cohorts were identified for inclusion, with a total of 4821 patients (2235 with low-risk, 1894 with intermediate-risk, and 446 with high-risk disease, when reported) treated with a variety of dose/fractionation schemes, permitting dose-response modeling. Five studies had a median follow-up of more than 5 years. Dosing regimens ranged from 32 to 50 Gy in 4 to 5 fractions, with total BED (α/β = 1.5 Gy) between 183.1 and 383.3 Gy. At 5 years, we found that in patients with low-intermediate risk disease, an equivalent doses of 2 Gy per fraction (EQD2) of 71 Gy (31.7 Gy in 5 fractions) achieved a TCP of 90% and an EQD2 of 90 Gy (36.1 Gy in 5 fractions) achieved a TCP of 95%. In patients with high-risk disease, an EQD2 of 97 Gy (37.6 Gy in 5 fractions) can achieve a TCP of 90% and an EQD2 of 102 Gy (38.7 Gy in 5 fractions) can achieve a TCP of 95%.

CONCLUSIONS

We found significant variation in the published literature on target delineation, margins used, dose/fractionation, and treatment schedule. Despite this variation, TCP was excellent. Most prescription doses range from 35 to 40 Gy, delivered in 4 to 5 fractions. The literature did not provide detailed dose-volume data, and our dosimetric analysis was constrained to prescription doses. There are many areas in need of continued research as SBRT continues to evolve as a treatment modality for prostate cancer, including the durability of local control with longer follow-up across risk groups, the efficacy and safety of SBRT as a boost to intensity modulated radiation therapy (IMRT), and the impact of incorporating novel imaging techniques into treatment planning.

Integrating Loco-Regional Hyperthermia Into the Current Oncology Practice: SWOT and TOWS Analyses

Moderate hyperthermia at temperatures between 40 and 44°C is a multifaceted therapeutic modality. It is a potent radiosensitizer, interacts favorably with a host of chemotherapeutic agents, and, in combination with radiotherapy, enforces immunomodulation akin to “in situ tumor vaccination.” By sensitizing hypoxic tumor cells and inhibiting repair of radiotherapy-induced DNA damage, the properties of hyperthermia delivered together with photons might provide a tumor-selective therapeutic advantage analogous to high linear energy transfer (LET) neutrons, but with less normal tissue toxicity. Furthermore, the high LET attributes of hyperthermia thermoradiobiologically are likely to enhance low LET protons; thus, proton thermoradiotherapy would mimic ¹²C ion therapy. Hyperthermia with radiotherapy and/or chemotherapy substantially improves therapeutic outcomes without enhancing normal tissue morbidities, yielding level I evidence reported in several randomized clinical trials, systematic reviews, and meta-analyses for various tumor sites. Technological advancements in hyperthermia delivery, advancements in hyperthermia treatment planning, online invasive and non-invasive MR-guided thermometry, and adherence to quality assurance guidelines have ensured safe and effective delivery of hyperthermia to the target region. Novel biological modeling permits integration of hyperthermia and radiotherapy treatment plans. Further, hyperthermia along with immune checkpoint inhibitors and DNA damage repair inhibitors could further augment the therapeutic efficacy resulting in synthetic lethality. Additionally, hyperthermia induced by magnetic nanoparticles coupled to selective payloads, namely, tumor-specific radiotheranostics (for both tumor imaging and radionuclide therapy), chemotherapeutic drugs, immunotherapeutic agents, and gene silencing, could provide a comprehensive tumor-specific theranostic modality akin to “magic (nano)bullets.” To get a realistic overview of the strength (S), weakness (W), opportunities (O), and threats (T) of hyperthermia, a SWOT analysis has been undertaken. Additionally, a TOWS analysis categorizes future strategies to facilitate further integration of hyperthermia with the current treatment modalities. These could gainfully accomplish a safe, versatile, and cost-effective enhancement of the existing therapeutic armamentarium to improve outcomes in clinical oncology.

Incorporating biological modeling into patient‐specific plan verification

Purpose

Dose–volume histogram (DVH) measurements have been integrated into commercially available quality assurance systems to provide a metric for evaluating accuracy of delivery in addition to gamma analysis. We hypothesize that tumor control probability and normal tissue complication probability calculations can provide additional insight beyond conventional dose delivery verification methods.

Methods

A commercial quality assurance system was used to generate DVHs of treatment plan using the planning CT images and patient‐specific QA measurements on a phantom. Biological modeling was performed on the DVHs produced by both the treatment planning system and the quality assurance system.

Results

The complication‐free tumor control probability, P₊, has been calculated for previously treated intensity modulated radiotherapy (IMRT) patients with diseases in the following sites: brain (−3.9% ± 5.8%), head‐neck (+4.8% ± 8.5%), lung (+7.8% ± 1.3%), pelvis (+7.1% ± 12.1%), and prostate (+0.5% ± 3.6%).

Conclusion

Dose measurements on a phantom can be used for pretreatment estimation of tumor control and normal tissue complication probabilities. Results in this study show how biological modeling can be used to provide additional insight about accuracy of delivery during pretreatment verification.

IMRT and brachytherapy comparison in gynaecological cancer treatment: thinking over dosimetry and radiobiology

Background

The role of radiotherapy and brachytherapy in the management of locally advanced cervical and endometrial cancer is well established. However, in some cases, intracavitary brachytherapy (ICBRT) is not recommended or cannot be carried out. We aimed to investigate whether external-beam irradiation delivered by means of intensity-modulated radiation therapy (IMRT) might replace ICBRT in gynaecological cancer when the standard ICBRT boost delivering cannot be administered for technical or clinical reasons.

Materials and methods

Fifteen already delivered treatments for gynaecological cancer patients were analysed. The treatments were performed through 3-dimensional conformal radiotherapy (3D-CRT) to the whole-pelvis up to the dose of 45–50.4 Gy followed by a boost dose administered with ICBRT in high-dose-rate or pulsed-dose-rate modality. For each patient, IMRT plans were elaborated to mimic the ICBRT. We analysed the ICBRT boost versus IMRT boost in terms of dosimetric and radiobiological aspects.

Results

Mean conformity index value calculated on boost volume was 0.73 for ICBRT and 0.97 for IMRT. Mean conformation number was 0.24 for ICBRT boost and 0.78 for IMRT boost. Mean normal tissue complication probability (NTCP) values for 3D-CRT plus ICBRT and for IMRT (pelvis plus boost) were, respectively, 28% and 5% for rectum; 1.5% and 0.1% for urinary bladder and 8.9% and 6.1% for bowel.

Conclusions

Our findings suggest that IMRT may represent a viable alternative in delivering the boost in patients diagnosed with gynaecological cancer not amenable to ICBRT.

Physical and Radiobiological Evaluation of Accelerated Intensity Modulated Radiotherapy for Locally Advanced Head and Neck Cancer and Comparison with Short-Term Clinical Outcomes

Objective:

The present study aims to evaluate the accelerated intensity modulated radiotherapy (IMRT) of head and neck (HandN) treatments using physical indices and radiobiological models with its clinical correlation using histogram analysis in radiation therapy (HART). The radiobiological evaluation in terms of tumor control probability (TCP) and normal tissue complication probability (NTCP) indices were compared with acute toxicity.

Materials and Methods:

A total of twenty patients with stage III and IV of HandN cases treated with accelerated IMRT using 6MV photons were chosen for the study. Using HART software, physical indices of the IMRT plans have been defined by universal plan indices (UPI’s) which summarize the various recognized plan indices. The overall quality factor (QF) of a plan was determined by a linear combination of all indices in UPI set. The clinical outcomes in terms of the acute toxicity like dysphagia and xerostomia were compared with NTCP values of the OAR calculated from HART software.

Results:

The mean QF and the mean Poisson TCP index was found to be 0.993±0.02 and 0.86 ±0.02 respectively. The mean JT Lyman NTCP index for bilateral parotid, constrictors, and larynx were found to be 0.23±0.14, 0.30±0.17 and 0.22±0.15 respectively. The acute toxicities in terms of severity of xerostomia and dysphagia have shown a moderate correlation with NTCP values of bilateral parotids, constrictors, and larynx, respectively.

Conclusion:

The mean QF based on UPI was found to be close to unity, which correlates with being a better IMRT plan. The present study suggested the existence of a moderate correlation between the calculated NTCP values and their respective severities of the organ at risk (OAR’s). Accelerated IMRT with chemotherapy is a clinically feasible option in the treatment of locally advanced head and neck squamous cell carcinoma (HNSCC) with encouraging initial tumor response and acceptable acute toxicities.

Task-based image quality assessment in radiation therapy: initial characterization and demonstration with computer-simulation study

In the majority of current radiation therapy (RT) applications, image quality is still assessed subjectively or by utilizing physical measures. A novel theory that applies objective task-based image quality assessment in radiation therapy (IQA-in-RT) was recently proposed, in which the area under the therapeutic operating characteristic curve (AUTOC) was employed as the figure-of-merit (FOM) for evaluating RT effectiveness. Although theoretically more appealing than conventional subjective or physical measures, a comprehensive implementation and evaluation of this novel task-based IQA-in-RT theory is required for its further application in improving clinical RT. In this work, a practical and modular IQA-in-RT framework is presented for implementing this theory for the assessment of imaging components on the basis of RT treatment outcomes. Computer-simulation studies are conducted to demonstrate the feasibility and utility of the proposed IQA-in-RT framework in optimizing x-ray computed tomography (CT) pre-treatment imaging, including the optimization of CT imaging dose and image reconstruction parameters. The potential advantages of optimizing imaging components in the RT workflow by use of the AUTOC as the FOM are also compared against those of other physical measures. The results demonstrate that optimization using the AUTOC leads to selecting different parameters from those indicated by physical measures, potentially improving RT performance. The sources of systemic randomness and bias that affect the determination of the AUTOC are also analyzed. The presented work provides a practical solution for the further investigation and analysis of the task-based IQA-in-RT theory and advances its applications in improving RT clinical practice and cancer patient care.

Comparison of Radiobiological Models for Radiation Therapy Plans of Prostate Cancer: Three-dimensional Conformal versus Intensity Modulated Radiation Therapy

Purpose:

In the current study, using different radiobiological models, tumor control probability (TCP) and normal tissue complication probability (NTCP) of radiotherapy plans were calculated for three-dimensional conformal radiation therapy (3D-CRT) and intensity modulated radiation therapy (IMRT) of prostate cancer.

Methods and Materials:

10 prostate plans were randomly selected among patients undergoing radiation therapy of prostate cancer. For each patient, 3D-CRT and IMRT plans were designed to deliver, on average 76 Gy and 82 Gy to planning target volume, respectively. Using different radiobiological models including Poisson, equivalent uniform dose (EUD) and Lyman-Kutcher-Burman (LKB), TCP and NTCP were calculated for prostate and critical organs including bladder, rectum and femoral heads.

Results:

IMRT plans provided significantly lower NTCP for bladder, rectum and femoral heads using LKB and EUD models (p-value <0.05). The EUD-calculated TCP for prostate cancer revealed no considerable improvement for IMRT plans relative to 3D-CRT plans. However, the TCPs calculated by Poisson model were dependent on α/β, and higher TCP for IMRT relative to 3D-CRT was seen for α/β higher than 5.

Conclusion:

It can be concluded that IMRT plans were superior to 3D-CRT plans in terms of estimated NTCP for studied critical organs. On the other hand, different mathematical models provided different quantitative outcome for TCP of prostate cancer plans. More clinical studies are suggested to confirm the accuracy of studied radiobiological models.

Objective assessment of the effects of tumor motion in radiation therapy

PURPOSE

Internal organ motion reduces the accuracy and efficacy of radiation therapy. However, there is a lack of tools to objectively (based on a medical or scientific task) assess the dosimetric consequences of motion, especially on an individual basis. We propose to use therapy operating characteristic (TOC) analysis to quantify the effects of motion on treatment efficacy for individual patients. We demonstrate the application of this tool with pancreatic stereotactic body radiation therapy (SBRT) clinical data and explore the origin of motion sensitivity.

METHODS

The technique is described as follows. (a) Use tumor-motion data measured from patients to calculate the motion-convolved dose of the gross tumor volume (GTV) and the organs at risk (OARs). (b) Calculate tumor control probability (TCP) and normal tissue complication probability (NTCP) from the motion-convolved dose-volume histograms. (c) Construct TOC curves from TCP and NTCP models. (d) Calculate the area under the TOC curve (AUTOC) and use it as a figure of merit for treatment efficacy. We used tumor motion data measured from patients to calculate the relation between AUTOC and motion magnitude for 25 pancreatic SBRT treatment plans. Furthermore, to explore the driving factor of motion sensitivity of a given plan, we compared the dose distribution of motion-sensitive plans and motion-robust plans and studied the dependence of motion sensitivity to motion directions.

RESULTS

Our technique is able to recognize treatment plans that are sensitive to motion. Under the presence of motion, the treatment efficacy of some plans changes from providing high tumor control and low risks of complications to providing no tumor control and high risks of side effects. Several treatment plans experience falloffs in AUTOC at a smaller magnitude of motion than other plans. In our dataset, a potential indicator of a motion-sensitive treatment plan is that the duodenum is in proximity to the tumor in the SI direction.

CONCLUSIONS

The TOC framework can serve as a tool to quantify the effects of internal organ motion in radiation therapy. With pancreatic SBRT clinical data, we applied this tool to study the change in treatment efficacy induced by motion for individual treatment plans. This framework could potentially be used clinically to understand the effects of motion in an individual patient and to design a patient-specific motion management plan. This framework could also be used in research to evaluate different components of the treatment process, such as motion-management techniques, treatment-planning algorithms, and treatment margins.

Evaluation of plan optimisers in prostate VMAT using the dose distribution index

Purpose:

Dose distribution index (DDI) is a treatment planning evaluation parameter, reflecting dosimetric information of target coverage that can help to spare organs at risk (OARs) and remaining volume at risk (RVR). The index has been used to evaluate and compare prostate volumetric modulated arc therapy (VMAT) plans using two different plan optimisers, namely photon optimisation (PO) and its predecessor, progressive resolution optimisation (PRO).

Materials and methods:

Twenty prostate VMAT treatment plans were created using the PO and PRO in this retrospective study. The 6 MV photon beams and a dose prescription of 78 Gy/39 fractions were used in plans with the same dose–volume criteria for plan optimisation. Dose–volume histograms (DVHs) of the planning target volume (PTV), as well as of OARs such as the rectum, bladder, left and right femur were determined in each plan. DDIs were calculated and compared for plans created by the PO and PRO based on DVHs of the PTV and all OARs.

Results:

The mean DDI values were 0·784 and 0·810 for prostate VMAT plans created by the PO and PRO, respectively. It was found that the DDI of the PRO plan was about 3·3% larger than the PO plan, which means that the dose distribution of the target coverage and sparing of OARs in the PRO plan was slightly better. Changing the weighting factors in different OARs would vary the DDI value by ∼7%. However, for plan comparison based on the same set of dose–volume criteria, the effect of weighting factor can be neglected because they were the same in the PO and PRO.

Conclusions:

Based on the very similar DDI values calculated from the PO and PRO plans, with the DDI value in the PRO plan slightly larger than that of the PO, it may be concluded that the PRO can create a prostate VMAT plan with slightly better dose distribution regarding the target coverage and sparing of OARs. Moreover, we found that the DDI is a simple and comprehensive dose–volume parameter for plan evaluation considering the target, OARs and RVR.

Dosimetric assessment of tumor control probability in intensity and volumetric modulated radiotherapy plans

OBJECTIVE:

Radiobiological models have been used to calculate the outcomes of treatment plans based on dose-volume relationship. This study examines several radiobiological models for the calculation of tumor control probability (TCP) of intensity modulated radiotherapy plans for the treatment of lung, prostate, and head and neck (H&N) cancers.

METHODS:

Dose volume histogram (DVH) data from the intensity modulated radiotherapy plans of 36 lung, 26 prostate, and 87  H&N cases were evaluated. The Poisson, Niemierko, and Marsden models were used to calculate the TCP of each disease group treatment plan. The calculated results were analyzed for correlation and discrepancy among the three models, as well as different treatment sites under study.

RESULTS:

The median value of calculated TCP in lung plans was 61.9% (34.1-76.5%), 59.5% (33.5-73.9%) and 32.5% (0.0-93.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in prostate plans was 85.1% (56.4-90.9%), 81.2% (56.1-88.7%) and 62.5% (28.2-75.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in H&N plans was 94.0% (44.0-97.8%) and 94.3% (0.0-97.8%) with the Poisson and Niemierko models, respectively. There were significant differences between the calculated TCPs with the Marsden model in comparison with either the Poisson or Niemierko model (p < 0.001) for both lung and prostate plans. The TCPs calculated by the Poisson and Niemierko models were significantly correlated for all three tumor sites.

CONCLUSION:

There are variations with different radiobiological models. Understanding of the correlation and limitation of a TCP model with dosimetric parameters can help develop the meaningful objective functions for plan optimization, which would lead to the implementation of outcome-based planning. More clinical data are needed to refine and consolidate the model for accuracy and robustness.

ADVANCES IN KNOWLEDGE:

This study has tested three radiobiological models with varied disease sites. It is significant to compare different models with the same data set for better understanding of their clinical applicability.

Radiobiological Evaluation of Three Common Clinical Radiotherapy Techniques Including Combined Photon-Electron, Tangential Beams and Electron Therapy in Left-Sided Mastectomy Patients

Background:

The aim of this study was radiobiological evaluation of different radiotherapy (RT) techniques, namely, combined photon-electron, two tangential photon beams, and electron therapy which are commonly used for treatment of mastectomy patients.

Materials and Methods:

The mentioned techniques were planned on the computed tomography (CT) images of a chest phantom, using TiGRT treatment planning system (TPS). The TPS dose calculations were verified using Thermo Luminescence dosimeters (TLD) measurements. Dose-volume histogram (DVH) of the plans was generated in the TPS, and also tumor control probability (TCP) and normal tissue complication probability (NTCP) values were calculated using DVH data for each technique. For TCP and NTCP modeling, Poisson Linear-Quadatric (PLQ) and Lyman-Kutcher-Burman (LKB) models were used, respectively.

Results:

The TCPs for the chest wall, internal mammary nodes, supraclavicular nodes, and axilla for the combined photon-electron was 90%, 90%, 90%, and 65%, respectively, which was higher compared to tangential beams (up to 11%, 11%, 5%, and 5%, respectively) and the electron therapy (up to 11%, 11%, 33%, and 23%, respectively) Whereas the NTCPs of the tangential beams for ipsilateral and contralateral lungs, heart, and chest wall–lung interface was 4%, 1%, 3%, and 5.6%, respectively. These NTCP values were considerably lower than electron therapy (up to 42%, 66%, and 40% and 30%, respectively) and combined photon-electron (up to 55%, 75%, 50%, and 20%, respectively) methods.

Conclusion:

Tangential beam is suggested for treating mastectomy patients, due to sufficient value of TCP, and also lower NTCP compared to the other techniques such as electron therapy and combined photon-electron.

The effects of radiotherapy on the survival of patients with unresectable non-small cell lung cancer

INTRODUCTION

Lung cancer represents the leading cause of cancer mortality across the worlds. At present, less than 30% of the patients can undergo curative surgery, while the majority of them (65%) are diagnosed with metastatic disease and directed to systemic treatments. In this context there is a subset of patients (25%) with locally advanced stage disease whose outcome might be improved by using combined strategies of treatment including chemotherapy, radiotherapy and surgery. Areas covered: Here we reviewed possible combination strategies aimed to improve the outcome of lung cancer patients, focusing on the role of radiotherapy both in the adjuvant and oligo-metastatic setting and in synergy with immunotherapy, and finally, we afforded the new challenges concerning the advanced RT and precision oncology. We carried out a focused analysis concerning the key clinical management weaknesses as well as the potential that current research holds. Expert commentary: We believe that the most promising clinical trials in this specific patient subset will build their rationale on the results of well-designed translational models aimed to test the combination of cytotoxic drugs, radiobiology, and immune-pharmacology. In this context, remarkable investigational fields are focused on the attempt to combine radiotherapy with chemo-immunological strategies and precision medicine protocols.

Impact of time-related factors on biologically accurate radiotherapy treatment planning

BACKGROUND

The incomplete repair (IR) model expresses the cell repair effect from radiation-induced damage over time, which is given little consideration in actual treatment planning. By incorporating the IR model into the normal tissue complication probability (NTCP), the accuracy and safety of treatment plan evaluations concerning the effect of repair can be improved. This study aims to evaluate the impact of incorporating the IR model into the NTCP by varying time-related factors such as the repair half-time (T_1/2) and the junction-shift sc3hedule in craniospinal irradiation (CSI).

METHODS

CSI was planned retrospectively, and the NTCP of the spinal cord was calculated with the IR model for values of T_1/2 from 1 to 10 h. The NTCP in the case of changing the junction-shift schedule was also examined in the same manner.

RESULTS

The NTCP with the IR model increased with increasing T_1/2, which is prominent for the larger T_1/2. By changing the junction-shift schedule, the NTCP with the IR model decreased when adjacent fields overlapped.

CONCLUSIONS

The IR model is a valuable addition to treatment planning because it enables the NTCP to be evaluated including the effect of repair and differences in scheduling to be reflected in the NTCP. However, these are largely dependent on the value of the T_1/2.

Relating the proton relative biological effectiveness to tumor control and normal tissue complication probabilities assuming interpatient variability in α/β

BACKGROUND

Proton therapy uses a constant relative biological effectiveness (RBE) of 1.1. The use of variable RBE values has been suggested but is currently not feasible due to uncertainties. The impact of variable RBE has solely been studied using dosimetric indices. This work elucidates the impact of RBE variations on tumor control and normal tissue complication probabilities (TCP/NTCP).

METHODS

Models to estimate TCP and NTCP were used in combination with an empirical proton RBE model. Variations in outcome as a function of linear-quadratic model parameters for cellular radiosensitivity were determined for TCP in prostate and ependymoma. In addition, NTCP analysis was done for brainstem necrosis.

RESULTS

Considering a variable proton RBE as a dose-modifying factor for prescription doses and dose constraints is misleading, as TCP/NTCP do not simply scale with RBE. The dependency of RBE on α/β cannot be interpreted independent of TCP/NTCP because variations in radiosensitivity affect both photon and proton treatments. Assuming interpatient variability in radiosensitivity results in lower TCP for patients with low α/β. In proton therapy, the magnitude of TCP variations is reduced due to an RBE increase as α/β decreases. The TCP in proton therapy is less affected by interpatient variability in α/β. On the other hand, patients with a lower α/β would have a lower complication probability, which is counteracted by an increase in RBE as α/β decreases. Toxicities in proton therapy would be more affected by α/β variations compared to photon therapy.

CONCLUSIONS

Assessment of variable RBE in proton therapy should be based on TCP and NTCP. Potential interpatient variability in radiosensitivity causes a smaller variance in TCP but a larger variance in NTCP for proton patients. The relative TCP as a function of α/β was found to be higher than the RBE, whereas the relative NTCP was lower than a calculated RBE.

Dosimetric and radiobiological comparison for quality assurance of IMRT and VMAT plans

Introduction

The gamma analysis used for quality assurance of a complex radiotherapy plan examines the dosimetric equivalence between planned and measured dose distributions within some tolerance. This study explores whether the dosimetric difference is correlated with any radiobiological difference between delivered and planned dose.

Methods

VMAT or IMRT plans optimized for 14 cancer patients were calculated and delivered to a QA device. Measured dose was compared against planned dose using 2‐D gamma analysis. Dose volume histograms (for various patient structures) obtained by interpolating measured data were compared against the planned ones using a 3‐D gamma analysis. Dose volume histograms were used in the Poisson model to calculate tumor control probability for the treatment targets and in the Sigmoid dose–response model to calculate normal tissue complication probability for the organs at risk.

Results

Differences in measured and planned dosimetric data for the patient plans passing at ≥94.9% rate at 3%/3 mm criteria are not statistically significant. Average ± standard deviation tumor control probabilities based on measured and planned data are 65.8±4.0% and 67.8±4.1% for head and neck, and 71.9±2.7% and 73.3±3.1% for lung plans, respectively. The differences in tumor control probabilities obtained from measured and planned dose are statistically insignificant. However, the differences in normal tissue complication probabilities for larynx, lungs‐GTV, heart, and cord are statistically significant for the patient plans meeting ≥94.9% passing criterion at 3%/3 mm.

Conclusion

A ≥90% gamma passing criterion at 3%/3 mm cannot assure the radiobiological equivalence between planned and delivered dose. These results agree with the published literature demonstrating the inadequacy of the criterion for dosimetric QA and suggest for a tighter tolerance.

Modeling tumor control probability for spatially inhomogeneous risk of failure based on clinical outcome data

PURPOSE

Objectives of this work are (1) to derive a general clinically relevant approach to model tumor control probability (TCP) for spatially variable risk of failure and (2) to demonstrate its applicability by estimating TCP for patients planned for photon and proton irradiation.

METHODS AND MATERIALS

The approach divides the target volume into sub-volumes according to retrospectively observed spatial failure patterns. The product of all sub-volume TCP_i values reproduces the observed TCP for the total tumor. The derived formalism provides for each target sub-volume i the tumor control dose (D_50,i) and slope (γ_50,i) parameters at 50% TCP_i. For a simultaneous integrated boost (SIB) prescription for 45 advanced head and neck cancer patients, TCP values for photon and proton irradiation were calculated and compared. The target volume was divided into gross tumor volume (GTV), surrounding clinical target volume (CTV), and elective CTV (CTVE). The risk of a local failure in each of these sub-volumes was taken from the literature.

RESULTS

Convenient expressions for D_50,i and γ_50,i were provided for the Poisson and the logistic model. Comparable TCP estimates were obtained for photon and proton plans of the 45 patients using the sub-volume model, despite notably higher dose levels (on average +4.9%) in the low-risk CTVE for photon irradiation. In contrast, assuming a homogeneous dose response in the entire target volume resulted in TCP estimates contradicting clinical experience (the highest failure rate in the low-risk CTVE) and differing substantially between photon and proton irradiation.

CONCLUSIONS

The presented method is of practical value for three reasons: It (a) is based on empirical clinical outcome data; (b) can be applied to non-uniform dose prescriptions as well as different tumor entities and dose-response models; and (c) is provided in a convenient compact form. The approach may be utilized to target spatial patterns of local failures observed in patient cohorts by prescribing different doses to different target regions. Its predictive power depends on the uncertainty of the employed established TCP parameters D₅₀ and γ₅₀ and to a smaller extent on that of the clinically observed pattern of failure risk.

3D radiobiological evaluation of combined radiotherapy and hyperthermia treatments

PURPOSE

Currently, clinical decisions regarding thermoradiotherapy treatments are based on clinical experience. Quantification of the radiosensitising effect of hyperthermia allows comparison of different treatment strategies, and can support clinical decision-making regarding the optimal treatment. The software presented here enables biological evaluation of thermoradiotherapy plans through calculation of equivalent 3D dose distributions.

METHODS

Our in-house developed software (X-Term) uses an extended version of the linear-quadratic model to calculate equivalent radiation dose, i.e. the radiation dose yielding the same effect as the thermoradiotherapy treatment. Separate sets of model parameters can be assigned to each delineated structure, allowing tissue specific modelling of hyperthermic radiosensitisation. After calculation, the equivalent radiation dose can be evaluated according to conventional radiotherapy planning criteria. The procedure is illustrated using two realistic examples. First, for a previously irradiated patient, normal tissue dose for a radiotherapy and thermoradiotherapy plan (with equal predicted tumour control) is compared. Second, tumour control probability (TCP) is assessed for two (otherwise identical) thermoradiotherapy schedules with different time intervals between radiotherapy and hyperthermia.

RESULTS

The examples demonstrate that our software can be used for individualised treatment decisions (first example) and treatment optimisation (second example) in thermoradiotherapy. In the first example, clinically acceptable doses to the bowel were exceeded for the conventional plan, and a substantial reduction of this excess was predicted for the thermoradiotherapy plan. In the second example, the thermoradiotherapy schedule with long time interval was shown to result in a substantially lower TCP.

CONCLUSIONS

Using biological modelling, our software can facilitate the evaluation of thermoradiotherapy plans and support individualised treatment decisions.

A complication probability planning study to predict the safety of a new protocol for intracranial tumour radiotherapy in dogs

Technical advances make it possible to deliver radiation therapy for canine intracranial tumours in fewer fractions, under the assumption of equivalent tumour control. With the aim of estimating the late toxicity risk profile for various tumour sizes and locations, the present paper evaluates the normal tissue complication probability (NTCP) values for the intracranial organs at risk. By making isoeffect calculations, a new 10-fraction radiation protocol was developed with the same tumour control probability (TCP) as a currently used 20-fraction standard protocol, and complication risk profiles for brain, brainstem and optic chiasm were modelled using a representative population of 64 dogs with brain tumours. For >59% of cases, the new 10-fraction protocol yielded an acceptable, low risk estimate of late toxicity (<10%). Our calculations suggest that it may be safe to treat small to intermediate-sized tumours that are neither located near the optic chiasm nor at the brainstem with 10 daily fractions of 4.35 Gy.

Therapy operating characteristic curves: tools for precision chemotherapy

The therapy operating characteristic (TOC) curve, developed in the context of radiation therapy, is a plot of the probability of tumor control versus the probability of normal-tissue complications as the overall radiation dose level is varied, e.g., by varying the beam current in external-beam radiotherapy or the total injected activity in radionuclide therapy. This paper shows how TOC can be applied to chemotherapy with the administered drug dosage as the variable. The area under a TOC curve (AUTOC) can be used as a figure of merit for therapeutic efficacy, analogous to the area under an ROC curve (AUROC), which is a figure of merit for diagnostic efficacy. In radiation therapy, AUTOC can be computed for a single patient by using image data along with radiobiological models for tumor response and adverse side effects. The mathematical analogy between response of observers to images and the response of tumors to distributions of a chemotherapy drug is exploited to obtain linear discriminant functions from which AUTOC can be calculated. Methods for using mathematical models of drug delivery and tumor response with imaging data to estimate patient-specific parameters that are needed for calculation of AUTOC are outlined. The implications of this viewpoint for clinical trials are discussed.

Assessment of radiobiological metrics applied to patient-specific QA process of VMAT prostate treatments

VMAT is a powerful technique to deliver hypofractionated prostate treatments. The lack of correlations between usual 2D pretreatment QA results and the clinical impact of possible mistakes has allowed the development of 3D verification systems. Dose determination on patient anatomy has provided clinical predictive capability to patient-specific QA process. Dose-volume metrics, as evaluation criteria, should be replaced or complemented by radiobiological indices. These metrics can be incorporated into individualized QA extracting the information for response parameters (gEUD, TCP, NTCP) from DVHs. The aim of this study is to assess the role of two 3D verification systems dealing with radiobiological metrics applied to a prostate VMAT QA program. Radiobiological calculations were performed for AAPM TG-166 test cases. Maximum differences were 9.3% for gEUD, -1.3% for TCP, and 5.3% for NTCP calculations. Gamma tests and DVH-based comparisons were carried out for both systems in order to assess their performance in 3D dose determination for prostate treatments (high-, intermediate-, and low-risk, as well as prostate bed patients). Mean gamma passing rates for all structures were bet-ter than 92.0% and 99.1% for both 2%/2 mm and 3%/3 mm criteria. Maximum discrepancies were (2.4% ± 0.8%) and (6.2% ± 1.3%) for targets and normal tis-sues, respectively. Values for gEUD, TCP, and NTCP were extracted from TPS and compared to the results obtained with the two systems. Three models were used for TCP calculations (Poisson, sigmoidal, and Niemierko) and two models for NTCP determinations (LKB and Niemierko). The maximum mean difference for gEUD calculations was (4.7% ± 1.3%); for TCP, the maximum discrepancy was (-2.4% ± 1.1%); and NTCP comparisons led to a maximum deviation of (1.5% ± 0.5%). The potential usefulness of biological metrics in patient-specific QA has been explored. Both systems have been successfully assessed as potential tools for evaluating the clinical outcome of a radiotherapy treatment in the scope of pretreatment QA.

Radiobiological evaluation of intensity modulated radiation therapy treatments of patients with head and neck cancer: A dual-institutional study

In clinical practice, evaluation of clinical efficacy of treatment planning stems from the radiation oncologist's experience in accurately targeting tumors, while keeping minimal toxicity to various organs at risk (OAR) involved. A more objective, quantitative method may be raised by using radiobiological models. The purpose of this work is to evaluate the potential correlation of OAR-related toxicities to its radiobiologically estimated parameters in simultaneously integrated boost (SIB) intensity modulated radiation therapy (IMRT) plans of patients with head and neck tumors at two institutions. Lyman model for normal tissue complication probability (NTCP) and the Poisson model for tumor control probability (TCP) models were used in the Histogram Analysis in Radiation Therapy (HART) analysis. In this study, 33 patients with oropharyngeal primaries in the head and neck region were used to establish the correlation between NTCP values of (a) bilateral parotids with clinically observed rates of xerostomia, (b) esophagus with dysphagia, and (c) larynx with dysphagia. The results of the study indicated a strong correlation between the severity of xerostomia and dysphagia with Lyman NTCP of bilateral parotids and esophagus, respectively, but not with the larynx. In patients without complications, NTCP values of these organs were negligible. Using appropriate radiobiological models, the presence of a moderate to strong correlation between the severities of complications with NTCP of selected OARs suggested that the clinical outcome could be estimated prior to treatment.

Dosimetric Effects of Magnetic Resonance Imaging-assisted Radiotherapy Planning: Dose Optimization for Target Volumes at High Risk and Analytic Radiobiological Dose Evaluation

Based on the assumption that apparent diffusion coefficients (ADCs) define high-risk clinical target volume (aCTVHR) in high-grade glioma in a cellularity-dependent manner, the dosimetric effects of aCTVHR-targeted dose optimization were evaluated in two intensity-modulated radiation therapy (IMRT) plans. Diffusion-weighted magnetic resonance (MR) images and ADC maps were analyzed qualitatively and quantitatively to determine aCTVHR in a high-grade glioma with high cellularity. After confirming tumor malignancy using the average and minimum ADCs and ADC ratios, the aCTVHR with double- or triple-restricted water diffusion was defined on computed tomography images through image registration. Doses to the aCTVHR and CTV defined on T1-weighted MR images were optimized using a simultaneous integrated boost technique. The dosimetric benefits for CTVs and organs at risk (OARs) were compared using dose volume histograms and various biophysical indices in an ADC map-based IMRT (IMRTADC) plan and a conventional IMRT (IMRTconv) plan. The IMRTADC plan improved dose conformity up to 15 times, compared to the IMRTconv plan. It reduced the equivalent uniform doses in the visual system and brain stem by more than 10% and 16%, respectively. The ADC-based target differentiation and dose optimization may facilitate conformal dose distribution to the aCTVHR and OAR sparing in an IMRT plan.

A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy

The aim of this work was to develop a framework for modeling organ effects within TOPAS (TOol for PArticle Simulation), a wrapper of the Geant4 Monte Carlo toolkit that facilitates particle therapy simulation. The DICOM interface for TOPAS was extended to permit contour input, used to assign voxels to organs. The following dose response models were implemented: The Lyman-Kutcher-Burman model, the critical element model, the population based critical volume model, the parallel-serial model, a sigmoid-based model of Niemierko for normal tissue complication probability and tumor control probability (TCP), and a Poisson-based model for TCP. The framework allows easy manipulation of the parameters of these models and the implementation of other models. As part of the verification, results for the parallel-serial and Poisson model for x-ray irradiation of a water phantom were compared to data from the AAPM Task Group 166. When using the task group dose-volume histograms (DVHs), results were found to be sensitive to the number of points in the DVH, with differences up to 2.4%, some of which are attributable to differences between the implemented models. New results are given with the point spacing specified. When using Monte Carlo calculations with TOPAS, despite the relatively good match to the published DVH's, differences up to 9% were found for the parallel-serial model (for a maximum DVH difference of 2%) and up to 0.5% for the Poisson model (for a maximum DVH difference of 0.5%). However, differences of 74.5% (in Rectangle1), 34.8% (in PTV) and 52.1% (in Triangle) for the critical element, critical volume and the sigmoid-based models were found respectively. We propose a new benchmark for verification of organ effect models in proton therapy. The benchmark consists of customized structures in the spread out Bragg peak plateau, normal tissue, tumor, penumbra and in the distal region. The DVH's, DVH point spacing, and results of the organ effect models are provided. The models were used to calculate dose response for a Head and Neck patient to demonstrate functionality of the new framework and indicate the degree of variability between the models in proton therapy.

Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

PURPOSE

To assess the impact of approximations in current analytical dose calculation methods (ADCs) on tumor control probability (TCP) in proton therapy.

METHODS

Dose distributions planned with ADC were compared with delivered dose distributions as determined by Monte Carlo simulations. A total of 50 patients were investigated in this analysis with 10 patients per site for 5 treatment sites (head and neck, lung, breast, prostate, liver). Differences were evaluated using dosimetric indices based on a dose-volume histogram analysis, a γ-index analysis, and estimations of TCP.

RESULTS

We found that ADC overestimated the target doses on average by 1% to 2% for all patients considered. The mean dose, D95, D50, and D02 (the dose value covering 95%, 50% and 2% of the target volume, respectively) were predicted within 5% of the delivered dose. The γ-index passing rate for target volumes was above 96% for a 3%/3 mm criterion. Differences in TCP were up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head and neck, and lung patients, respectively. Differences in normal tissue complication probabilities for bladder and anterior rectum of prostate patients were less than 3%.

CONCLUSION

Our results indicate that current dose calculation algorithms lead to underdosage of the target by as much as 5%, resulting in differences in TCP of up to 11%. To ensure full target coverage, advanced dose calculation methods like Monte Carlo simulations may be necessary in proton therapy. Monte Carlo simulations may also be required to avoid biases resulting from systematic discrepancies in calculated dose distributions for clinical trials comparing proton therapy with conventional radiation therapy.

Quantifying and Reducing Uncertainties in Cancer Therapy

There are two basic sources of uncertainty in cancer chemotherapy: how much of the therapeutic agent reaches the cancer cells, and how effective it is in reducing or controlling the tumor when it gets there. There is also a concern about adverse effects of the therapy drug. Similarly in external-beam radiation therapy or radionuclide therapy, there are two sources of uncertainty: delivery and efficacy of the radiation absorbed dose, and again there is a concern about radiation damage to normal tissues. The therapy operating characteristic (TOC) curve, developed in the context of radiation therapy, is a plot of the probability of tumor control vs. the probability of normal-tissue complications as the overall radiation dose level is varied, e.g. by varying the beam current in external-beam radiotherapy or the total injected activity in radionuclide therapy. The TOC can be applied to chemotherapy with the administered drug dosage as the variable. The area under a TOC curve (AUTOC) can be used as a figure of merit for therapeutic efficacy, analogous to the area under an ROC curve (AUROC), which is a figure of merit for diagnostic efficacy. In radiation therapy AUTOC can be computed for a single patient by using image data along with radiobiological models for tumor response and adverse side effects. In this paper we discuss the potential of using mathematical models of drug delivery and tumor response with imaging data to estimate AUTOC for chemotherapy, again for a single patient. This approach provides a basis for truly personalized therapy and for rigorously assessing and optimizing the therapy regimen for the particular patient. A key role is played by Emission Computed Tomography (PET or SPECT) of radiolabeled chemotherapy drugs.